Antibacterial evaluation of Salvia miltiorrhizae on Escherichia coli by microcalorimetry coupled with chemometrics
© The Author(s) 2017
Received: 6 February 2017
Accepted: 2 March 2017
Published: 17 March 2017
For seeking novel antibacterial agents with high efficacy and low toxicity to deal with drug resistance, the effects of Salvia miltiorrhizae from various sources on Escherichia coli were evaluated by microcalorimetry coupled with chemometrics. Firstly, the heat-flow power-time curves of E. coli growth affected by different S. miltiorrhizae samples were recorded. Then, some crucial quantitative thermo-kinetic parameters including growth rate constant, heat-flow power and heat output, etc. were obtained from theses curves and were further investigated by some powerful chemometric techniques including similarity analysis, multivariate analysis of variance, hierarchical clustering analysis and principle component analysis. By analyzing the principle parameters, growth rate constant of the second exponential phase (k 2) and the heat-flow output powers of the second highest peak (P 2), together with the derived parameter inhibitory ratio (I, %), it could be quickly concluded that the tested S. miltiorrhizae samples from different sources in China exhibited strong antibacterial effects on E. coli and the samples from Beijing city exhibited the strongest anti-E. coli effects, which might be used as novel and underlying antibacterial candidates for the resistance of E. coli to the existing drugs in practice. This study provides a useful tool and helpful idea to accurately and rapidly evaluate the antibacterial effects of some complex matrices, offering some references for exploring new antibacterial agents.
KeywordsSalvia miltiorrhizae Escherichia coli Microcalorimetry Chemometrics Antibacterial evaluation
In recent decades, more and more attentions have been paid on Traditional Chinese Medicines (TCMs) because of their complementary therapeutic efficacy to Western medicines, and their abilities to solve some primary problems that have not yet been solved by traditional therapy, such as resistance of some microbes to the existing antibacterial agents which has led to increasing challenges for doctors and researchers, as well as has become an increasingly important and pressing global attention (Zhao et al. 2015). Therefore, developing new antibacterial agents from TCMs has become the major focus.
Escherichia coli, a kind of gram-negative bacteria that were widely existed in the environment, which have brought serious hazards to the intestinal tract of humans and animals to cause various infections and foodborne diseases such as peritonitis, cholecystitis, cystitis, bloody and non-bloody diarrhea, and so on (Müller et al. 2001). These pathogenic E. coli are responsible for hemolytic colitis infections that lead to the hemolytic uremic syndrome, and also result in high levels of morbidity and mortality in general population, especially for impressionable groups including infants, children, and the elderly (Kong et al. 2012). So, developing new antibacterial agents with high efficacy and low toxicity for the resistant E. coli is in great urgency.
As a well-known and important medicinal plant derived from the dried root of Salvia miltiorrhizae Bge., Salvia miltiorrhizae (Danshen in Chinese) has been officially recorded in Chinese pharmacopoeia for the treatment of cardiovascular diseases, inflammation, mental and liver diseases (Guo et al. 2014; Zhang et al. 2016; Zhou et al. 2005). The main bioactive components of S. miltiorrhizae such as hydrophilic phenolic acids and lipophilic diterpenoid tanshinone have been proven to express widely antibacterial activities with potential applications in medicinal industry (Wang et al. 2007; Zhao et al. 2011).
Microcalorimetry has been used successfully to evaluate the antibacterial effects of TCMs with high sensitivity, accuracy, and low time-consuming (Zhao et al. 2014). During the metabolic growth processes, a flow of thermal effect is generated, which can be recorded by a microcalorimeter and is directly related to an increase or decrease in the power release by different sources. For recording the evolution of energetic intensity, the microcalorimetric tool shows special advantages compared with conventional techniques of biological investigation, such as disk diffusion method (Wu et al. 2013). By means of analyzing the heat-flow power (HFP)-time curves of microbial metabolic growth recorded by the microcalorimeter, the thermokinetic parameters such as growth rate constant (k), heat output (Q) and heat-flow power (P) can be obtained, and the effects of other substances on microbes can be further well and effectively evaluated and compared by analyzing the changes of these parameters (Braissant et al. 2013, 2015; Chen et al. 2013; Zhao et al. 2015) in combination with some powerful chemometric approaches such as similarity analysis (SA), multivariate analysis of variance (MANOVA), hierarchical clustering analysis (HCA) and principle component analysis (PCA).
To the best of our knowledge, antibacterial evaluation and comparison of S. miltiorrhizae from various sources on the growth of various microbe sources by using the microcalorimetric technique has not been reported. The purpose of this study was to determine the antibacterial activities of S. miltiorrhizae on E. coli by using microcalorimetry coupled with some helpful chemometric methods including SA, MANOVA, HCA and PCA. The results have shown that the microcalorimetric technique was a potential and powerful tool to effectively investigate and evaluate the antibacterial activities of TCMs and S. miltiorrhizae with high efficacy and low toxicity can be used as a novel and underlying antibacterial candidate for the resistance of E. coli to the existing drugs.
Materials and methods
Plant materials and chemicals
Thermokinetic parameters obtained from the heat-flow power-time curves of E. coli growth affect by S. Miltiorrhizae samples
k 1 (min−1)
P 2 (mW)
Q 1 (J)
Q 2 (J)
Bacterial strains and culture media
The strain of E. coli (CCTCC AB91112) was provided by China Center for Type Culture Collection, Wuhan University, Wuhan, P.R. China. Firstly, E. coli were inoculated into 25 mL broth culture medium which contained 10 g peptone, 6 g beef extract and 5 g NaCl in 1000 mL purified water (pH7.0-7.2) and was sterilized by autoclaving at 0.1 MPa and 121 °C for 30 min. Then, the 100 mL wide-mouthed glass bottle containing inoculated medium was incubated in a ZWFR-200 shaker (Shanghai, China) for 8 h at 37 °C at the rotation speed of 110 rpm. The flask was sealed up with parafilm for limiting the quantity of oxygen because E. coli is a kind of facultative anaerobe. After incubation, the bacteria were transferred into the Luria–Bertani (LB) culture medium which was prepared by 10 g tryptone, 5 g yeast extract, and 5 g NaCl dissolving in 1000 mL of purified water (pH7.0–7.2). The LB culture medium was also sterilized by the same above-mentioned condition and stored in a refrigerator at 4 °C for next biothermodynamics investigation of E. coli by microcalorimetry.
About 0.2 g dried S. miltiorrhizae powder (through a 50-mesh sieve) was dissolving by 20 mL 80% MeOH in a 50-mL centrifuge tube and the weight of the tube while sealed up with parafilm was recorded. The tube containing the sample solution was transferred into an ultra-sonic water bath for extraction for 30 min at room temperature. After ultrasonication, the lost weight was made up before following centrifugation at 4000 rpm for 10 min. Next, the supernatant was transferred into a new 30-mL centrifuge tube and stored at 4 °C in the dark until the microcalorimetric measurement.
A 3114/3236 TAM air microcalorimeter (Thermometric AB, Sweden) was used for recording the heat-flow power-time (HFP-t) curves of E. coli growth in the absence (the control) or presence of S. miltiorrhizae solution through ampoule method in batch mode. The microcalorimeter was brought to equilibrium temperature overnight in advance. Four-milliliter LB culture medium containing the E. coli suspensions at the cell density of 1 × 106 colony forming units (CFU)/mL was introduced into each 20-mL sterilized ampoule. Then, 1 mL of S. miltiorrhizae solution was added. Correspondingly, the ampoule containing E. coli suspension without the sample solution was set as the control group. Afterwards, the ampoules containing only E. coli suspension and one of the 32 batches of S. miltiorrhizae sample solutions at the final concentration of 10 mg/mL were sealed, shaken-up slightly, and put into the microcalorimeter. Subsequently, after a balance of the instrument for minutes to 37 °C, the HFP-t curves were recorded continuously by Thermometric AB program using the dedicated software package at an interval of 1 min until the curves returned to the baseline. All the experiments were operated in super-clean worktable at 37 °C.
In reference to the idea and application of similarity analysis (SA) on the chromatographic fingerprints of TCMs (Zhai et al. 2014; Qin et al. 2015), in this study, SA was introduced for intuitively evaluating the similarities of the changing trends of HFP-t curves of E. coli growth affected by S. miltiorrhizae from different sources based on the original data from these curves. The correlation coefficient for similarity among the HFP-t curves was calculated by cosin method by using the software of Windows SPSS Inc. version 18.0 (Chicago, IL, USA).
Multivariate analysis of variance
As a widely-used statistic method for comparing between-group information, the multivariate analysis of variance (MANOVA) is applied to observe whether there were differences of the antibacterial activities of multi-regional S. miltiorrhizae on E. coli. P (probability parameter) <0.05 is regarded as statistically significant. The software of Windows SPSS Inc. version 18.0 was used.
Hierarchical clustering analysis
Hierarchical clustering analysis (HCA) is one of the most commonly used approaches for multivariate analysis, which can classify the objects (samples) into classes (clusters) by means of measuring either the distance or the similarity between the objects. Each object within the same class is similar to the others but different from those in other classes based on a predetermined selection criterion (Zhuang et al. 2011). Heml is an easy-to-use tool with transformation and visualization of multi-dimensional data in a single heat map and can provide a concise but comprehensive presentation of biothermokinetics and multiple clustering strategies for analyzing the data (Deng et al. 2014). Additionally, this software can be recolored, rescaled in a customized manner for visualized evaluation. In this study, the software of Heml (Heat map Illustrator) version 1.0 for Windows (Wuhan, P.R. China) was used for HCA and a method called maximum linkage and the Kendall’s tau distance as metric was applied to establish clusters.
Principal component analysis
Too many parameters can be extracted from the heat-flow power-time curve of E. coli growth affected by S. miltiorrhizae samples from different regions, which will result in many difficulties for accurately assess the anti-E. coli effects. So, the statistical technology of principal component analysis (PCA) was introduced for next data extraction and analysis. As a multivariate data analysis method, PCA is widely used for searching some underlying factors from multidimensional data that play crucial roles from many confused information. It is an eigenvector-based multivariate analysis tool to explain variance of the multivariate data and further to reduce computation burden and transform the original multivariate data to a smaller and more succinct set of variables, namely principal components (PCs), with orthometric and uncorrelated natures (Zhao et al. 2014). As containing nearly all of the original information, PCs could express the maximal variability of the initial data in a graphical formation as a scores plot which could cluster the sample and further differentiate the samples from different sources according to their antibacterial effects, and the loadings plot allows identification of the main parameters (Wu et al. 2016). Then, the new parameter(s) which are farthest away from the main cluster of variables (parameters) are selected as the crucial indexes for next evaluation.
Here, PCA was operated on mean-normalized data of the nine quantitative parameters from the HFP-t curves of E. coli growth affected by different S. miltiorrhizae samples using software of Simca-P 11.5 (Umetrics AB, Umea, Sweden) (Kong et al. 2010).
Metabolic HFP-t curves of E. coli growth
Quantitative thermokinetic parameters for E. coli growth
where P 0 regards as the heat-output power at time t = 0, and P t represents the value of power at anytime during determination. P 1 and P 2 are the heat-flow output powers of the first and second exponential phase of E. coli growth, and t 1 and t 2 are the homologous appearance times. By plotting the logarithm of the HFP-t curve, another important thermokinetic parameter-growth rate constant (k) can be calculated from the slope of the line according to the above-listed equation. There are two exponential growth phases in all HFP-t curves, so the corresponding growth rate constant k 1 is for the first exponential growth phase and k 2 for the second one. Similarly, by integrating the areas under the HFP-t curves, Q 1 is the heat output of the first exponential growth phase, Q 2 is of the second exponential growth phase and Q s is the sum of the heat output of the whole growth processes. All these thermokinetic parameters including k 1, k 2, t 1, t 2, P 1, P 2, Q 1, Q 2 and Q s could be read from the HFP-t curves or calculated according to the above-referenced equation, which have been listed in Table 1. The value changes of these thermokinetic parameters could also quantitatively reflect the influence of S. miltiorrhizae on E. coli growth.
However, the bewildering changing trends of the complex quantitative parameters made it virtually difficult to draw a definitive conclusion on the antibacterial activities of S. miltiorrhizae samples from different sources. Therefore, introducing some powerful chemometric methods for simplifying the evaluation was necessary.
It could be found in Fig. 2 that compared with the control, the addition of S. miltiorrhizae sample solutions influenced the growth of E. coli, from the changes of the shape of HFP-t curves and the peak heights and appearance time of the two highest peaks. Then, SA was performed on the values of the nine parameters (k 1, k 2, t 1, t 2, P 1, P 2, Q 1, Q 2 and Q s) in Table 1. The results showed that correlation coefficients for similarity among the HFP-t curves of E. coli growth without (the control) and with each S. miltiorrhizae sample solution from different sources were presented as 0.756, 0.871, 0.858, 0.870, 0.856, 0.529, 0.868, 0.821, 0.880, 0.794, 0.839, 0.832, 0.827, 0.842, 0.831, 0.831, 0.839 for Guizhou province, 0.858, 0.863, 0.679, 0.872, 0.827, 0.862 for Sichuan province, 0.876, 0.743, 0.772, 0.824 for Shandong province, 0.798, 0.819, 0.744 for Henan province and 0.676, 0.587 for Beijing city. The differences of correlation coefficients illustrated various antibacterial activities of S. miltiorrhizae samples on E. coli growth. Small value of similarity indicated that the HFP-t curve of E. coli growth was significantly influenced by S. miltiorrhizae samples compared with the control. So, it could preliminarily inferred that S. miltiorrhizae samples from Beijing city had the strongest anti-E. coli effects. Nevertheless, it was not sufficient and accurate to evaluate the antibacterial activities only from the results of similarity analysis. So, a further multivariate analysis of variance for between-group information was carried out in the next part.
MANOVA results for all tested S. miltiorrhizae samples based on the nine thermokinetic quantitative parameters
Wilks’ Lambda value
Guizhou and Sichuan
Guizhou and Shandong
Guizhou and Henan
Guizhou and Beijing
Sichuan and Shandong
Sichuan and Henan
Sichuan and Beijing
Shandong and Henan
Shandong and Beijing
Henan and Beijing
Inhibitory ratio (I, %)
In this study, the antibacterial effects of S. Miltiorrhizae samples from different sources on E. coli were evaluated for the first time by microcalorimetry. Using this microcalorimetric method, some important information including the real-time HFP-t curves, as well as some quantitative thermokinetic parameters of E. coli growth affected by S. Miltiorrhizae samples was obtained at the same time, which could not be obtained by traditional microbiological methods (Klančnik et al. 2010; Ahmed et al. 2014). By analyzing the HFP-t curves and the thermokinetic parameters of E. coli growth affected by S. Miltiorrhizae samples using SA, MANOVA, HCA and PCA, it could be quickly found that S. Miltiorrhizae samples exhibited antibacterial effects on E. coli and the samples collected from Beijing city exhibited the strongest anti-E. coli effects, which might be used as novel and underlying antibacterial candidates for the resistance of E. coli to the existing drugs in the future.
This present study also showed that microcalorimetric technology offered some notable advantages for biological investigation compared with some traditional microbiological approaches. This tool could not only save more experiment time, but also exhibit satisfactory sensitivity, accuracy and reproducibility. By the combination of microcalorimetry and chemometrics, the antibacterial effects of other substances including TCMs could be accurately and quickly evaluated, providing a useful method and idea for further study in the light of developing new antibacterial agents with high activity and low toxicity.
In the ongoing study, more bacteria should be selected as the targets to confirm the antibacterial effects of S. Miltiorrhizae samples to provide more evidences for S. Miltiorrhizae as a novel antibacterial agent. In addition, the antibacterial mechanism of S. Miltiorrhizae on E. coli should also be classified for its following application in practice to deal with many essential problems that have not yet been solved due to drug resistance and tolerance after abusing medicines.
- S. miltiorrhizae :
- E. coli :
Traditional Chinese Medicine
multivariate analysis of variance
hierarchical clustering analysis
principle component analysis
colony forming units
GYY and SSZ carried out the experimental studies, participated in the experiments and drafted the manuscript. YLH carried out the analysis. WYG and WJK participated in the design of the study and performed the statistical analysis. MHY, PC and XRW conceived of the study, and participated in its design and coordination and helped to draft the manuscript. All authors read and approved the final manuscript.
The authors declare that they have no competing interests.
Availability of data and materials
All data in this manuscript were deposited in publicly available repositories in the Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
This work was supported from the National Natural Science Foundation of China (81473346, 81573595 and 81673593), CAMS Innovation Fund for Medical Sciences (CIFMS) (2016-I2M-3-010) and Beijing Natural Science Foundation (7152101).
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
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